GDPO Explained: NVIDIA Fixes GRPO for LLM Reinforcement Learning
NVIDIA recently introduced GDPO in a paper titled GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL
Optimization.
GDPO is a new reinforcement learning algorithm designed to fix GRPO’s limitations in multi-reward LLM training.
In this video, we explain how GDPO works, why standard GRPO fails with multiple rewards, and how reward-decoupled normalization improves advantage estimation and model performance.
Written Review - https://aipapersacademy.com/gdpo/
Paper - https://arxiv.org/abs/2601.05242
Code - https://github.com/NVlabs/GDPO
GRPO Deep Dive - https://aipapersacademy.com/deepseekm...
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The video was edited using VideoScribe - https://tidd.ly/44TZEiX
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Chapters:
0:00 Introduction
1:51 GRPO Recap
3:30 Multi-Reward GRPO
4:30 GRPO Reward Collapse
6:00 GDPO's Fix
7:26 GDPO Results